tslumley

setClass("ggthing", representation(content="call"))
setClass("ggthings",representation(contents="list"))


bracket<-function(e1) NULL
setGeneric("bracket")

setMethod("bracket",c("ggthing"),
  function(e1){
  	new("ggthings",contents=list(e1@content))

tslumley

d<-strsplit("Northland		
No Motor Vehicle	3792	4077
One Motor Vehicle	20229	22161
Two Motor Vehicles	19578	20652
Three or More Motor Vehicles	7398	7407
Waitemata		
No Motor Vehicle	8871	8658
One Motor Vehicle	54753	57492
Two Motor Vehicles	66411	72768
Three or More Motor Vehicles	29757	33219

tslumley

---
title: "Multiple response"
author: "Thomas Lumley"
date: "7/23/2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

tslumley

library(AER)

svyivreg<-function(formula, design, ...) UseMethod("svyivreg",design)

svyivreg.survey.design<-function(formula, design){

    .data<-model.frame(design)
    .data$.weights<-weights(design,"sampling")
    model<- ivreg(formula, data=.data, weights=.weights)

tslumley

## https://doi.org/10.1093/jssam/smz010

make.s<-function(mu, sigma,tau2,alpha){
	g<-make.g(alpha)
	invg<-make.ginv(alpha)
	
	function(theta) invg(2*sigma*(theta-mu)/tau2)
}

make.g<-function(alpha){

tslumley

## startup
library(jsonlite)
library(httr)
library(knitr)
library(kableExtra)
options(stringsAsFactors=FALSE)

## These two files are part of the static GTFS information
routes<-read.csv("./routes.txt")
routes$route_id<-substr(as.character(routes$route_id),1,5) ## remove versioning info

tslumley

## from: https://www.stats.govt.nz/information-releases/property-transfer-statistics-march-2019-quarter
re<-read.table(text=
"year quarter citbuy citsell resbuy ressell fornbuy fornsell corpbuy corpsell knowbuy knowsell unkbuy unksell total
2017	Mar	23592	23490	2130	1101	621	375	3060	4407	29406	29370	4287	4320	33690
2017	Jun	30414	30678	3063	1512	930	486	4188	5946	38595	38625	450	426	39048
2017	Sep	27123	27021	2703	1458	783	441	3618	5316	34230	34239	126	117	34356
2017	Dec	28632	28125	2862	1491	1038	 468	3663	6111	 36195	36192	84	87	36279
2018	Mar	25881	25947	2625	1401	1083	501	3255	4998	32841	32847	39	36	32880
2018	Jun	31044	31173	3171	1656	1116	 492	4281	6285	 39606	39606	21	21	39627
2018	Sep	28284	27684	2982	1557	717	378	3630	5997	35613	35613	21	21	35634

tslumley

withPV<-function(mapping, design, action, ...) UseMethod("withPV",design)

withPV.survey.design<-function(mapping, design, action,...){
	
	if(inherits(mapping,"formula")) mapping<-list(mapping)
	
	if (!is.list(mapping)) 
		stop("'mapping' must be a list of formulas")
	
	if (!all(sapply(mapping, length)==3)) 

tslumley

library(shiny)

# Define UI for application that draws a histogram
ui <- fluidPage(
   
   # Application title
   titlePanel("Bayesian Surprise"),
   
   # Sidebar with a slider input for number of bins 

tslumley

# Based on https://gist.github.com/tjvananne/8b0e7df7dcad414e8e6d5bf3947439a9
# Rewritten to work chunk by chunk, so I can read the 42B file with only 8GB memory

    # input .txt file, exports list of list of values and character vector of names (words)
    proc_pretrained_vec <- function(filename, chunksize=1000, guess_size=100000) {
	size<-guess_size
        here<-0
	    
        # initialize space for values and the names of each word in vocab
        vals <- vector(mode = "list", length(size))